A persistent issue in the sensing system is the need to determine the structure of a scene, including objects seen at long distances using a mobile platform. Scene structure recovered in the range of 50 m-1000 m is useful for planning for autonomous mobility and mapping unobserved areas. Sensing from 100 m-2000 m is useful for reconnaissance, surveillance, and target acquisition (RSTA), target designation, and cueing automatic target recognition (ATR). The difficulty with using images from a moving platform is knowing the precise relationship (position and direction) between the cameras that acquired the images. In particular, the relative pointing angles between the cameras must be known to a milliradian or better.
A conventional approach is to use a laser range finder or LADAR, but these ranges require high power, and LADAR is emissive. So, the scene structure typically recovered from LADAR sensing has power/speed/resolution limitations at the ranges of interest (hundreds of meters to a kilometer or more).
Vision stereo with a fixed baseline can also be used to acquire range information. Accurate range estimates for objects that are a kilometer away, however, requires a 10 m baseline, which is impractical for a mobile, fixed-baseline system. Passive depth recovery at mid-ranges requires longer baselines than can be achieved by a practical fixed-baseline stereo system. So, scene structure recovered from conventional stereo vision systems have a fixed baseline that limits range and/or mobility of the stereo system.
Thus, a need exists in the art for an improved sensing system for estimating range and detecting the objects from large distances.